The power and limitations of gene expression pathway analyses toward predicting population response to environmental stressors

Evolutionary Applications
Brenna C M StanfordSean M Rogers

Abstract

Rapid environmental changes impact the global distribution and abundance of species, highlighting the urgency to understand and predict how populations will respond. The analysis of differentially expressed genes has elucidated areas of the genome involved in adaptive divergence to past and present environmental change. Such studies however have been hampered by large numbers of differentially expressed genes and limited knowledge of how these genes work in conjunction with each other. Recent methods (broadly termed "pathway analyses") have emerged that aim to group genes that behave in a coordinated fashion to a factor of interest. These methods aid in functional annotation and uncovering biological pathways, thereby collapsing complex datasets into more manageable units, providing more nuanced understandings of both the organism-level effects of modified gene expression, and the targets of adaptive divergence. Here, we reanalyze a dataset that investigated temperature-induced changes in gene expression in marine-adapted and freshwater-adapted threespine stickleback (Gasterosteus aculeatus), using Weighted Gene Co-expression Network Analysis (WGCNA) with PANTHER Gene Ontology (GO)-Slim overrepresentation and Kyoto Encyclopedia...Continue Reading

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Citations

Jul 21, 2020·Evolutionary Applications·Anne-Laure FerchaudMaren Wellenreuther
Apr 1, 2021·Journal of Comparative Physiology. B, Biochemical, Systemic, and Environmental Physiology·Matthew R J MorrisSean M Rogers

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Methods Mentioned

BETA
GTPase
transgenic

Software Mentioned

car
Ensembl
R package Pathview
PINE
KEGG
R package clusterProfiler
fastcluster
RegenDbase
R biomaRt package
WGCNA

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